arXiv subjects

A. Hourlier

Publications and source records attributed to A. Hourlier.

At least 19 recordsLinked to original sources

arXiv2025

First Measurement of Neutrino Emissions from Spent Nuclear Fuel by the Double Chooz Experiment

Neutrino emission from nuclear reactors provides real-time insights into reactor power and fuel evolution, with potential applications in monitoring and nuclear safeguards. Following reactor shutdown, a low-intensity flux of ``residual neutrinos'' persists due to the decay of long-lived fission isotopes in the partially burnt fuel remaining within the reactor cores and in spent nuclear fuel stored in nearby cooling pools. The Double Chooz experiment at the Chooz B nuclear power plant in France achieved the first quantitative measurement of this residual flux based on 17.2 days of reactor-off data. In the energy range where the residual signal is most pronounced, the neutrino detector located 400$\,$m from the cores recorded $106 \pm 18$ neutrino candidate events (5.9$\sigma$ significance). This measurement is in excellent agreement with the predicted value of $88 \pm 7$ events derived from detailed reactor simulations modeling the decay activities of fission products and incorporating the best-available models of neutrino spectra.

hep-ex↗

arXiv2023

Probing Earth's Missing Potassium using the Unique Antimatter Signature of Geoneutrinos

The formation of the Earth remains an epoch with mysterious puzzles extending to our still incomplete understanding of the planet's potential origin and bulk composition. Direct confirmation of the Earth's internal heat engine was accomplished by the successful observation of geoneutrinos originating from uranium (U) and thorium (Th) progenies, manifestations of the planet's natural radioactivity dominated by potassium (40K) and the decay chains of uranium (238U) and thorium (232Th). This radiogenic energy output is critical to planetary dynamics and must be accurately measured for a complete understanding of the overall heat budget and thermal history of the Earth. Detecting geoneutrinos remains the only direct probe to do so and constitutes a challenging objective in modern neutrino physics. In particular, the intriguing potassium geoneutrinos have never been observed and thus far have been considered impractical to measure. We propose here a novel approach for potassium geoneutrino detection using the unique antimatter signature of antineutrinos to reduce the otherwise overwhelming backgrounds to observing this rarest signal. The proposed detection framework relies on the innovative LiquidO detection technique to enable positron (e+) identification and antineutrino interactions with ideal isotope targets identified here for the first time. We also provide the complete experimental methodology to yield the first potassium geoneutrino discovery.

physics.geo-ph↗

arXiv2022

Observation of Radon Mitigation in MicroBooNE by a Liquid Argon Filtration System

The MicroBooNE liquid argon time projection chamber (LArTPC) maintains a high level of liquid argon purity through the use of a filtration system that removes electronegative contaminants in continuously-circulated liquid, recondensed boil off, and externally supplied argon gas. We use the MicroBooNE LArTPC to reconstruct MeV-scale radiological decays. Using this technique we measure the liquid argon filtration system's efficacy at removing radon. This is studied by placing a 500 kBq $^{222}$Rn source upstream of the filters and searching for a time-dependent increase in the number of radiological decays in the LArTPC. In the context of two models for radon mitigation via a liquid argon filtration system, a slowing mechanism and a trapping mechanism, MicroBooNE data supports a radon reduction factor of greater than 99.999% or 97%, respectively. Furthermore, a radiological survey of the filters found that the copper-based filter material was the primary medium that removed the $^{222}$Rn. This is the first observation of radon mitigation in liquid argon with a large-scale copper-based filter and could offer a radon mitigation solution for future large LArTPCs.

physics.ins-det↗

arXiv2022

Cosmic ray muon clustering for the MicroBooNE liquid argon time projection chamber using sMask-RCNN

In this article, we describe a modified implementation of Mask Region-based Convolutional Neural Networks (Mask-RCNN) for cosmic ray muon clustering in a liquid argon TPC and applied to MicroBooNE neutrino data. Our implementation of this network, called sMask-RCNN, uses sparse submanifold convolutions to increase processing speed on sparse datasets, and is compared to the original dense version in several metrics. The networks are trained to use wire readout images from the MicroBooNE liquid argon time projection chamber as input and produce individually labeled particle interactions within the image. These outputs are identified as either cosmic ray muon or electron neutrino interactions. We find that sMask-RCNN has an average pixel clustering efficiency of 85.9% compared to the dense network's average pixel clustering efficiency of 89.1%. We demonstrate the ability of sMask-RCNN used in conjunction with MicroBooNE's state-of-the-art Wire-Cell cosmic tagger to veto events containing only cosmic ray muons. The addition of sMask-RCNN to the Wire-Cell cosmic tagger removes 70% of the remaining cosmic ray muon background events at the same electron neutrino event signal efficiency. This event veto can provide 99.7% rejection of cosmic ray-only background events while maintaining an electron neutrino event-level signal efficiency of 80.1%. In addition to cosmic ray muon identification, sMask-RCNN could be used to extract features and identify different particle interaction types in other 3D-tracking detectors.

hep-ex↗

arXiv2022

MiniBooNE and MicroBooNE Combined Fit to a 3+1 Sterile Neutrino Scenario

This letter presents the results from the MiniBooNE experiment within a full "3+1" scenario where one sterile neutrino is introduced to the three-active-neutrino picture. In addition to electron-neutrino appearance at short-baselines, this scenario also allows for disappearance of the muon-neutrino and electron-neutrino fluxes in the Booster Neutrino Beam, which is shared by the MicroBooNE experiment. We present the 3+1 fit to the MiniBooNE electron-(anti)neutrino and muon-(anti)neutrino data alone, and in combination with MicroBooNE electron-neutrino data. The best-fit parameters of the combined fit with the exclusive CCQE analysis (inclusive analysis) are $\Delta m^2 = 0.29 eV^2 (0.33 eV^2)$, $|U_{e4}|^2 = 0.016 (0.500)$, $|U_{\mu 4}|^2 = 0.500 (0.500)$, and $\sin^2(2\theta_{\mu e})=0.0316 (1.0)$. Comparing the no-oscillation scenario to the 3+1 model, the data prefer the 3+1 model with a $\Delta \chi^2/\text{dof} = 24.7 / 3 (17.3 / 3)$, a $4.3\sigma (3.4\sigma)$ preference assuming the asymptotic approximation given by Wilks' theorem.

hep-ex↗

arXiv2021

Novel Approach for Evaluating Detector-Related Uncertainties in a LArTPC Using MicroBooNE Data

Primary challenges for current and future precision neutrino experiments using liquid argon time projection chambers (LArTPCs) include understanding detector effects and quantifying the associated systematic uncertainties. This paper presents a novel technique for assessing and propagating LArTPC detector-related systematic uncertainties. The technique makes modifications to simulation waveforms based on a parameterization of observed differences in ionization signals from the TPC between data and simulation, while remaining insensitive to the details of the detector model. The modifications are then used to quantify the systematic differences in low- and high-level reconstructed quantities. This approach could be applied to future LArTPC detectors, such as those used in SBN and DUNE.

hep-ex↗

arXiv2021

Search for an Excess of Electron Neutrino Interactions in MicroBooNE Using Multiple Final State Topologies

We present a measurement of electron neutrino interactions from the Fermilab Booster Neutrino Beam using the MicroBooNE liquid argon time projection chamber to address the nature of the excess of low energy interactions observed by the MiniBooNE collaboration. Three independent electron neutrino searches are performed across multiple single electron final states, including an exclusive search for two-body scattering events with a single proton, a semi-inclusive search for pion-less events, and a fully inclusive search for events containing all hadronic final states. With differing signal topologies, statistics, backgrounds, reconstruction algorithms, and analysis approaches, the results are found to be consistent with the nominal electron neutrino rate expectations from the Booster Neutrino Beam and no excess of electron neutrino events is observed.

hep-ex↗

arXiv2021

Search for an anomalous excess of charged-current $\nu_e$ interactions without pions in the final state with the MicroBooNE experiment

This article presents a measurement of $\nu_e$ interactions without pions in the final state using the MicroBooNE experiment and an investigation into the excess of low-energy electromagnetic events observed by the MiniBooNE collaboration. The measurement is performed in exclusive channels with (1$e$N$p$0$\pi$) and without (1$e$0$p$0$\pi$) visible final-state protons using 6.86$\times 10^{20}$ protons on target of data collected from the Booster Neutrino Beam at Fermilab. Events are reconstructed with the Pandora pattern recognition toolkit and selected using additional topological information from the MicroBooNE liquid argon time projection chamber. Using a goodness-of-fit test the data are found to be consistent with the predicted number of events with nominal flux and interaction models with a $p$-value of 0.098 in the two channels combined. A model based on the low-energy excess observed in MiniBooNE is introduced to quantify the strength of a possible $\nu_e$ excess. The analysis suggests that if an excess is present, it is not consistent with a simple scaling of the $\nu_e$ contribution to the flux. Combined, the 1$e$N$p$0$\pi$ and 1$e$0$p$0$\pi$ channels do not give a conclusive indication about the tested model, but separately they both disfavor the low-energy excess model at $>$90% CL. The observation in the most sensitive 1$e$N$p$0$\pi$ channel is below the prediction and consistent with no excess. In the less sensitive 1$e$0$p$0$\pi$ channel the observation at low energy is above the prediction, while overall there is agreement over the full energy spectrum.

hep-ex↗

arXiv2021

Wire-Cell 3D Pattern Recognition Techniques for Neutrino Event Reconstruction in Large LArTPCs: Algorithm Description and Quantitative Evaluation with MicroBooNE Simulation

Wire-Cell is a 3D event reconstruction package for liquid argon time projection chambers. Through geometry, time, and drifted charge from multiple readout wire planes, 3D space points with associated charge are reconstructed prior to the pattern recognition stage. Pattern recognition techniques, including track trajectory and $dQ/dx$ (ionization charge per unit length) fitting, 3D neutrino vertex fitting, track and shower separation, particle-level clustering, and particle identification are then applied on these 3D space points as well as the original 2D projection measurements. A deep neural network is developed to enhance the reconstruction of the neutrino interaction vertex. Compared to traditional algorithms, the deep neural network boosts the vertex efficiency by a relative 30\% for charged-current $\nu_e$ interactions. This pattern recognition achieves 80-90\% reconstruction efficiencies for primary leptons, after a 65.8\% (72.9\%) vertex efficiency for charged-current $\nu_e$ ($\nu_\mu$) interactions. Based on the resulting reconstructed particles and their kinematics, we also achieve 15-20\% energy reconstruction resolutions for charged-current neutrino interactions.

physics.ins-det↗

arXiv2021

New CC0\pi\ GENIE Model Tune for MicroBooNE

A novel tune has been made for the MicroBooNE experiment. The fit uses 4 new parameters within the GENIE v3.0.6 Monte Carlo program. Charged current pionless data from the T2K experiment was used. New uncertainties were obtained. These results will be used in future MicroBooNE analyses.

hep-ex↗

arXiv2021

Search for an anomalous excess of charged-current quasi-elastic $\nu_e$ interactions with the MicroBooNE experiment using Deep-Learning-based reconstruction

We present a measurement of the $\nu_e$-interaction rate in the MicroBooNE detector that addresses the observed MiniBooNE anomalous low-energy excess (LEE). The approach taken isolates neutrino interactions consistent with the kinematics of charged-current quasi-elastic (CCQE) events. The topology of such signal events has a final state with 1 electron, 1 proton, and 0 mesons ($1e1p$). Multiple novel techniques are employed to identify a $1e1p$ final state, including particle identification that use two methods of deep-learning-based image identification, and event isolation using a boosted decision-tree ensemble trained to recognize two-body scattering kinematics. This analysis selects 25 $\nu_e$-candidate events in the reconstructed neutrino energy range of 200--1200\,MeV, while $29.0 \pm 1.9_\text{(sys)} \pm 5.4_\text{(stat)}$ are predicted when using $\nu_\mu$ CCQE interactions as a constraint. We use a simplified model to translate the MiniBooNE LEE observation into a prediction for a $\nu_e$ signal in MicroBooNE. A $\Delta \chi^2$ test statistic, based on the combined Neyman--Pearson $\chi^2$ formalism, is used to define frequentist confidence intervals for the LEE signal strength. Using this technique, in the case of no LEE signal, we expect this analysis to exclude a normalization factor of 0.75 (0.98) times the median MiniBooNE LEE signal strength at 90\% ($2\sigma$) confidence level, while the MicroBooNE data yield an exclusion of 0.25 (0.38) times the median MiniBooNE LEE signal strength at 90\% ($2\sigma$) confidence

hep-ex↗

arXiv2021

Search for an anomalous excess of inclusive charged-current $\nu_e$ interactions in the MicroBooNE experiment using Wire-Cell reconstruction

We report a search for an anomalous excess of inclusive charged-current (CC) $\nu_e$ interactions using the Wire-Cell event reconstruction package in the MicroBooNE experiment, which is motivated by the previous observation of a low-energy excess (LEE) of electromagnetic events from the MiniBooNE experiment. With a single liquid argon time projection chamber detector, the measurements of $\nu_{\mu}$ CC interactions as well as $\pi^0$ interactions are used to constrain signal and background predictions of $\nu_e$ CC interactions. A data set collected from February 2016 to July 2018 corresponding to an exposure of 6.369 $\times$ 10$^{20}$ protons on target from the Booster Neutrino Beam at FNAL is analyzed. With $x$ representing an overall normalization factor and referred to as the LEE strength parameter, we select 56 fully contained $\nu_e$ CC candidates while expecting 69.6 $\pm$ 8.0 (stat.) $\pm$ 5.0 (sys.) and 103.8 $\pm$ 9.0 (stat.) $\pm$ 7.4 (sys.) candidates after constraints for the absence (eLEE$_{x=0}$) of the median signal strength derived from the MiniBooNE observation and the presence (eLEE$_{x=1}$) of that signal strength, respectively. Under a nested hypothesis test using both rate and shape information in all available channels, the best-fit $x$ is determined to be 0 (eLEE$_{x=0}$) with a 95.5% confidence level upper limit of $x$ at 0.502. Under a simple-vs-simple hypotheses test, the eLEE$_{x=1}$ hypothesis is rejected at 3.75$\sigma$, while the eLEE$_{x=0}$ hypothesis is shown to be consistent with the observation at 0.45$\sigma$. In the context of the eLEE model, the estimated 68.3% confidence interval of the $\nu_e$ hypothesis to explain the LEE observed in the MiniBooNE experiment is disfavored at a significance level of more than 2.6$\sigma$ (3.0$\sigma$) considering MiniBooNE's full (statistical) uncertainties.

hep-ex↗

arXiv2021

First Measurement of Energy-Dependent Inclusive Muon Neutrino Charged-Current Cross Sections on Argon with the MicroBooNE Detector

We report a measurement of the energy-dependent total charged-current cross section $\sigma\left(E_\nu\right)$ for inclusive muon neutrinos scattering on argon, as well as measurements of flux-averaged differential cross sections as a function of muon energy and hadronic energy transfer ($\nu$). Data corresponding to 5.3$\times$10$^{19}$ protons on target of exposure were collected using the MicroBooNE liquid argon time projection chamber located in the Fermilab Booster Neutrino Beam with a mean neutrino energy of approximately 0.8 GeV. The mapping between the true neutrino energy $E_\nu$ and reconstructed neutrino energy $E^{rec}_\nu$ and between the energy transfer $\nu$ and reconstructed hadronic energy $E^{rec}_{had}$ are validated by comparing the data and Monte Carlo (MC) predictions. In particular, the modeling of the missing hadronic energy and its associated uncertainties are verified by a new method that compares the $E^{rec}_{had}$ distributions between data and an MC prediction after constraining the reconstructed muon kinematic distributions, energy and polar angle, to those of data. The success of this validation gives confidence that the missing energy in the MicroBooNE detector is well-modeled and underpins first-time measurements of both the total cross section $\sigma\left(E_\nu\right)$ and the differential cross section $d\sigma/d\nu$ on argon.

hep-ex↗

arXiv2021

MiniBooNE Data Releases

The MiniBooNE experiment has provided data releases for most publications. Occasionally it is necessary to move data release pages. This document provides a single point of reference that will be updated by the collaboration to point to the present location of the MiniBooNE data releases.

hep-ex↗

arXiv2021

Electromagnetic Shower Reconstruction and Energy Validation with Michel Electrons and $\pi^0$ Samples for the Deep-Learning-Based Analyses in MicroBooNE

This article presents the reconstruction of the electromagnetic activity from electrons and photons (showers) used in the MicroBooNE deep learning-based low energy electron search. The reconstruction algorithm uses a combination of traditional and deep learning-based techniques to estimate shower energies. We validate these predictions using two $\nu_{\mu}$-sourced data samples: charged/neutral current interactions with final state neutral pions and charged current interactions in which the muon stops and decays within the detector producing a Michel electron. Both the neutral pion sample and Michel electron sample demonstrate agreement between data and simulation. Further, the absolute shower energy scale is shown to be consistent with the relevant physical constant of each sample: the neutral pion mass peak and the Michel energy cutoff.

hep-ex↗

arXiv2021

Search for Neutrino-Induced Neutral Current $\Delta$ Radiative Decay in MicroBooNE and a First Test of the MiniBooNE Low Energy Excess Under a Single-Photon Hypothesis

We report results from a search for neutrino-induced neutral current (NC) resonant $\Delta$(1232) baryon production followed by $\Delta$ radiative decay, with a $\langle0.8\rangle$~GeV neutrino beam. Data corresponding to MicroBooNE's first three years of operations (6.80$\times$10$^{20}$ protons on target) are used to select single-photon events with one or zero protons and without charged leptons in the final state ($1\gamma1p$ and $1\gamma0p$, respectively). The background is constrained via an in-situ high-purity measurement of NC $\pi^0$ events, made possible via dedicated $2\gamma1p$ and $2\gamma0p$ selections. A total of 16 and 153 events are observed for the $1\gamma1p$ and $1\gamma0p$ selections, respectively, compared to a constrained background prediction of $20.5 \pm 3.65 \text{(sys.)} $ and $145.1 \pm 13.8 \text{(sys.)} $ events. The data lead to a bound on an anomalous enhancement of the normalization of NC $\Delta$ radiative decay of less than $2.3$ times the predicted nominal rate for this process at the 90% confidence level (CL). The measurement disfavors a candidate photon interpretation of the MiniBooNE low-energy excess as a factor of $3.18$ times the nominal NC $\Delta$ radiative decay rate at the 94.8% CL, in favor of the nominal prediction, and represents a greater than $50$-fold improvement over the world's best limit on single-photon production in NC interactions in the sub-GeV neutrino energy range

hep-ex↗

arXiv2021

First Measurement of Inclusive Electron-Neutrino and Antineutrino Charged Current Differential Cross Sections in Charged Lepton Energy on Argon in MicroBooNE

We present the first measurement of the single-differential $\nu_e + \bar{\nu}_e$ charged-current inclusive cross sections on argon in electron or positron energy and in electron or positron scattering cosine over the full angular range. Data were collected using the MicroBooNE liquid argon time projection chamber located off-axis from the Fermilab Neutrinos at the Main Injector beam over an exposure of $2.0\times10^{20}$ protons on target. The signal definition includes a 60 MeV threshold on the $\nu_e$ or $\bar{\nu}_e$ energy and a 120 MeV threshold on the electron or positron energy. The measured total and differential cross sections are found to be in agreement with the GENIE, NuWro, and GiBUU neutrino generators.

hep-ex↗

arXiv2021

Calorimetric classification of track-like signatures in liquid argon TPCs using MicroBooNE data

The MicroBooNE liquid argon time projection chamber located at Fermilab is a neutrino experiment dedicated to the study of short-baseline oscillations, the measurements of neutrino cross sections in liquid argon, and to the research and development of this novel detector technology. Accurate and precise measurements of calorimetry are essential to the event reconstruction and are achieved by leveraging the TPC to measure deposited energy per unit length along the particle trajectory, with mm resolution. We describe the non-uniform calorimetric reconstruction performance in the detector, showing dependence on the angle of the particle trajectory. Such non-uniform reconstruction directly affects the performance of the particle identification algorithms which infer particle type from calorimetric measurements. This work presents a new particle identification method which accounts for and effectively addresses such non-uniformity. The newly developed method shows improved performance compared to previous algorithms, illustrated by a 94% proton selection efficiency and a 10% muon mis-identification rate, with a fairly loose selection of tracks performed on beam data. The performance is further demonstrated by identifying exclusive final states in $\nu_{\mu} CC$ interactions. While developed using MicroBooNE data and simulation, this method is easily applicable to future LArTPC experiments, such as SBND, ICARUS, and DUNE.

physics.ins-det↗